SPIRIT: Low Power Seizure Prediction using Unsupervised Online-Learning and Zoom Analog Frontends
- URL: http://arxiv.org/abs/2409.04838v2
- Date: Mon, 11 Nov 2024 03:37:16 GMT
- Title: SPIRIT: Low Power Seizure Prediction using Unsupervised Online-Learning and Zoom Analog Frontends
- Authors: Aviral Pandey, Adelson Chua, Ryan Kaveh, Justin Doong, Rikky Muller,
- Abstract summary: This work presents SPIRIT: eight-gradient-based Predictor with Integrated Retraining and In situ accuracy Tuning.
SPIRIT is a complete system-on-a-chip (SoC) integrating an unsupervised online-learning seizure prediction classifier with 14.4 uW, 0.057 mm2, 90.5 dB dynamic range, Zoom Analog Frontends.
Through its online learning algorithm, prediction accuracy improves by up to 15%, and prediction times extend by up to 7x, without any external intervention.
- Score: 0.0
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Early prediction of seizures and timely interventions are vital for improving patients' quality of life. While seizure prediction has been shown in software-based implementations, to enable timely warnings of upcoming seizures, prediction must be done on an edge device to reduce latency. Ideally, such devices must also be low-power and track long-term drifts to minimize maintenance from the user. This work presents SPIRIT: Stochastic-gradient-descent-based Predictor with Integrated Retraining and In situ accuracy Tuning. SPIRIT is a complete system-on-a-chip (SoC) integrating an unsupervised online-learning seizure prediction classifier with eight 14.4 uW, 0.057 mm2, 90.5 dB dynamic range, Zoom Analog Frontends. SPIRIT achieves, on average, 97.5%/96.2% sensitivity/specificity respectively, predicting seizures an average of 8.4 minutes before they occur. Through its online learning algorithm, prediction accuracy improves by up to 15%, and prediction times extend by up to 7x, without any external intervention. Its classifier consumes 17.2 uW and occupies 0.14 mm2, the lowest reported for a prediction classifier by >134x in power and >5x in area. SPIRIT is also at least 5.6x more energy efficient than the state-of-the-art.
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